These examples, and the new documentation page, are extremely helpful. Thank you /very/ much. I’m continuing to read / digest / modify them to get a better understanding, but they’ve already cleared up a lot for me.

One thing that popped out was the use of |Flow.transform()|. The difference between |map| and |transform| is now clear to me, but I then started to question the difference between a |Stage| and a |Flow|, and they now confuse me a bit… (if this is covered somewhere, please forgive me). Why is a |Stage| not a derived type of |Flow|? Or, perhaps another way to say that is, Why do |Stage|s exist at all? It feels like there are |Flow|s, |BidiFlow|s and |Graph|s. |Stage| feels like it’s just another manifestation of a |Flow|, perhaps an earlier part of the design that may not need to be there?

P.S. It looks like the stream-composition doc is missing something in the |attributes| section. The diagram shows that |nestedSource| is connected to |nestedSink| but the code doesn’t do such a thing. Did you mean to add a |nestedSource.to(nestedSink)|?

Akka Team <mailto:[email protected]>
July 29, 2015 at 9:28 AM
And now I added another version where the server just streams random numbers until the client disconnects, then it closes the connection. It needed a custom stage though to make emitting from an Iterable interruptible (mapConcat does not interrupt on completion, only on errors).




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Endre Varga <mailto:[email protected]>
July 29, 2015 at 7:59 AM
I now updated the gist with the reverse direction: Now a client sends a String command and expects an Iterable[Int] back as a response. I currently limited the funcionality to one request per connection, since otherwise I would need a bit more elaborate codec which would complicate the example (I would need to add a delimiter between the iterables on the wire. Not too hard to add it though). It still shows how these things are supposed to work.

-Endre


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Akka Team <mailto:[email protected]>
July 29, 2015 at 7:14 AM
Hi Derek,

It is not that hard, but you need to develop a certain kind of intuition to attack these problems. I very much recommend the new documentation page http://doc.akka.io/docs/akka-stream-and-http-experimental/1.0/scala/stream-composition.html as it helps to visualize the ideas.

I created a sample app that does what you want, you can find the gist here: https://gist.github.com/drewhk/25bf7472db04b5699b80

The features in that app:
- exposes the client API as a Source[Int, Unit]. Anytime you materialize that source and send it data, it will open a TCP connection and dump the integers to the server, then closes the connection - exposes the server API as a Source[(InetSocketAddress, Iterable[Int]), Future[ServerBinding]]. It will provide you with a continuous stream of client address, client data iterable pairs. - includes a simple codec pair for encoding the Ints. It is kind of stupid for this use case, but it works.

Some notes:
- draining the client data to an Iterable might be suboptimal if the Iterables are large, in this case a Source[Int] would be a better abstraction - the implementation caps the size of the Iterable but currently just silently ignores overflows (I was lazy to build a stage or use fold for this sample, so I used grouped())

-Endre





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Derek Wyatt <mailto:[email protected]>
July 26, 2015 at 3:12 PM
Hi,

I'm still trying to figure out the best way to work with TCP flows and, while I've got something working, this seems really quite wrong, so there's gotta be a better way.

What I want to do is send an Iterable[Int] from the client to the server and have the server materialize that resulting flow in a Future[Iterable[Int]].


||
val bytesStage =// elided... BidiFlow of serialization and framing

val serverValuePromise =Promise[Seq[AnyRef]]()

// Technically, the materialized value isn't important, since it's actually going to be pulled out
// via the Promise
val serverConsumerFlow:Flow[AnyRef,AnyRef,Future[Seq[AnyRef]]]=Flow.wrap(
// Consume the client's stream and complete the serverValuePromise with its folded result Sink.fold(Vector.empty[AnyRef])((acc,v:AnyRef)=>acc :+v).mapMaterializedValue(v =>{serverValuePromise.completeWith(v);v }),
// We're not sending anything from this side
Source.empty)(Keep.left)

// The server
val serverSide:Future[ServerBinding]=StreamTcp().bindAndHandle(serverConsumerFlow.join(bytesStage),"0.0.0.0",0,halfClose =true)

// We really want to stop listening once the client has successfully connected, but this is good
// enough
serverValuePromise.future.onComplete {
case_ =>
    serverSide.onSuccess {
casebinding =>binding.unbind()
}
}

// I need the endpoint where the client needs to connect
val destination =Await.result(serverSide,1.second).localAddress

// Get the source running
Source((1to 10).map(newInteger(_))).via(bytesStage.joinMat(StreamTcp().outgoingConnection(destination))(Keep.right)).to(Sink.ignore).run()

// Print out what the client has sent to the server
Await.result(serverValuePromise.future,1.second).foreach(t =>println(s"tt: $t"))

I tried doing this the other way around - where the server side supplies source - but this caused me issues with actually shutting down the socket. Having the client do it seems to make shutting down the socket on completion of the source, just naturally occur. The problem with the server side providing the source was that the client source needed to finish "properly". If I created it as `empty` then it would kill things too quickly. If I then created it as a n Actor source that just didn't do anything, I couldn't find a decent way to close it.

There's gotta be a better way to do this, but I'm too much of a noob to see it. Can anyone improve this code for me?

Thanks,
Derek



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